e faecalis atcc 19433t Search Results


e durans  (ATCC)
93
ATCC e durans
E Durans, supplied by ATCC, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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e faecalis atcc 19433  (ATCC)
97
ATCC e faecalis atcc 19433
Bacterial strains and plasmids used in this study
E Faecalis Atcc 19433, supplied by ATCC, used in various techniques. Bioz Stars score: 97/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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pathogens  (ATCC)
99
ATCC pathogens
Bacterial strains and plasmids used in this study
Pathogens, supplied by ATCC, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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enterococcus faecalis  (ATCC)
99
ATCC enterococcus faecalis
(A) Schematic representation of an artificial neuron. The neuron is a simple processing unit connected to other neurons by synapses. A synaptic weight (wi) is associated with each synapsis. An output y is produced by using the weighted sum (z = Σxiwi) of its inputs (xi; x0 is fixed, and the product x0w0 is known as bias) as an argument of the activation function f(z). Different types of activation functions (nonlinear sigmoid functions as the logistic and hyperbolic tangent, but also threshold or linear functions) can be used. (B) Architecture of the ANNs used in this study. All types of networks used as an input the number of bands in selected molecular weight (in kilobases) intervals of the RAPD-PCR patterns and had three output nodes, one for each of the three species to be identified (EFM, E. faecium; EFS, E. <t>faecalis;</t> and ST, S. thermophilus). Both the MLP and the BN had a hidden layer with five nodes and used hyperbolic tangent activation functions, but they differed in the algorithm used to iteratively adjust the synaptic weights during supervised training (see the text for details). The hidden layer of the RBF was made up of 25 centers. For each of these, the Euclidean distance between an input pattern and the center was used as an argument of a nonlinear radial basis function, and the result was passed to the output nodes, which in turn had a linear activation function. The number and coordinates of the centers in the input space and the synaptic weights of the output neurons were adjusted during supervised training.
Enterococcus Faecalis, supplied by ATCC, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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faecium atcc 19434t fusr rifr  (ATCC)
97
ATCC faecium atcc 19434t fusr rifr
(A) Schematic representation of an artificial neuron. The neuron is a simple processing unit connected to other neurons by synapses. A synaptic weight (wi) is associated with each synapsis. An output y is produced by using the weighted sum (z = Σxiwi) of its inputs (xi; x0 is fixed, and the product x0w0 is known as bias) as an argument of the activation function f(z). Different types of activation functions (nonlinear sigmoid functions as the logistic and hyperbolic tangent, but also threshold or linear functions) can be used. (B) Architecture of the ANNs used in this study. All types of networks used as an input the number of bands in selected molecular weight (in kilobases) intervals of the RAPD-PCR patterns and had three output nodes, one for each of the three species to be identified (EFM, E. faecium; EFS, E. <t>faecalis;</t> and ST, S. thermophilus). Both the MLP and the BN had a hidden layer with five nodes and used hyperbolic tangent activation functions, but they differed in the algorithm used to iteratively adjust the synaptic weights during supervised training (see the text for details). The hidden layer of the RBF was made up of 25 centers. For each of these, the Euclidean distance between an input pattern and the center was used as an argument of a nonlinear radial basis function, and the result was passed to the output nodes, which in turn had a linear activation function. The number and coordinates of the centers in the input space and the synaptic weights of the output neurons were adjusted during supervised training.
Faecium Atcc 19434t Fusr Rifr, supplied by ATCC, used in various techniques. Bioz Stars score: 97/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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enterococcus faecalis  (DSMZ)
93
DSMZ enterococcus faecalis
(A) Schematic representation of an artificial neuron. The neuron is a simple processing unit connected to other neurons by synapses. A synaptic weight (wi) is associated with each synapsis. An output y is produced by using the weighted sum (z = Σxiwi) of its inputs (xi; x0 is fixed, and the product x0w0 is known as bias) as an argument of the activation function f(z). Different types of activation functions (nonlinear sigmoid functions as the logistic and hyperbolic tangent, but also threshold or linear functions) can be used. (B) Architecture of the ANNs used in this study. All types of networks used as an input the number of bands in selected molecular weight (in kilobases) intervals of the RAPD-PCR patterns and had three output nodes, one for each of the three species to be identified (EFM, E. faecium; EFS, E. <t>faecalis;</t> and ST, S. thermophilus). Both the MLP and the BN had a hidden layer with five nodes and used hyperbolic tangent activation functions, but they differed in the algorithm used to iteratively adjust the synaptic weights during supervised training (see the text for details). The hidden layer of the RBF was made up of 25 centers. For each of these, the Euclidean distance between an input pattern and the center was used as an argument of a nonlinear radial basis function, and the result was passed to the output nodes, which in turn had a linear activation function. The number and coordinates of the centers in the input space and the synaptic weights of the output neurons were adjusted during supervised training.
Enterococcus Faecalis, supplied by DSMZ, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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l lactis subsp lactis atcc 19435t  (ATCC)
96
ATCC l lactis subsp lactis atcc 19435t
(A) Schematic representation of an artificial neuron. The neuron is a simple processing unit connected to other neurons by synapses. A synaptic weight (wi) is associated with each synapsis. An output y is produced by using the weighted sum (z = Σxiwi) of its inputs (xi; x0 is fixed, and the product x0w0 is known as bias) as an argument of the activation function f(z). Different types of activation functions (nonlinear sigmoid functions as the logistic and hyperbolic tangent, but also threshold or linear functions) can be used. (B) Architecture of the ANNs used in this study. All types of networks used as an input the number of bands in selected molecular weight (in kilobases) intervals of the RAPD-PCR patterns and had three output nodes, one for each of the three species to be identified (EFM, E. faecium; EFS, E. <t>faecalis;</t> and ST, S. thermophilus). Both the MLP and the BN had a hidden layer with five nodes and used hyperbolic tangent activation functions, but they differed in the algorithm used to iteratively adjust the synaptic weights during supervised training (see the text for details). The hidden layer of the RBF was made up of 25 centers. For each of these, the Euclidean distance between an input pattern and the center was used as an argument of a nonlinear radial basis function, and the result was passed to the output nodes, which in turn had a linear activation function. The number and coordinates of the centers in the input space and the synaptic weights of the output neurons were adjusted during supervised training.
L Lactis Subsp Lactis Atcc 19435t, supplied by ATCC, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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fmoc 5 amino valeric acid 5 ava  (Chem Impex International)
95
Chem Impex International fmoc 5 amino valeric acid 5 ava
(A) Schematic representation of an artificial neuron. The neuron is a simple processing unit connected to other neurons by synapses. A synaptic weight (wi) is associated with each synapsis. An output y is produced by using the weighted sum (z = Σxiwi) of its inputs (xi; x0 is fixed, and the product x0w0 is known as bias) as an argument of the activation function f(z). Different types of activation functions (nonlinear sigmoid functions as the logistic and hyperbolic tangent, but also threshold or linear functions) can be used. (B) Architecture of the ANNs used in this study. All types of networks used as an input the number of bands in selected molecular weight (in kilobases) intervals of the RAPD-PCR patterns and had three output nodes, one for each of the three species to be identified (EFM, E. faecium; EFS, E. <t>faecalis;</t> and ST, S. thermophilus). Both the MLP and the BN had a hidden layer with five nodes and used hyperbolic tangent activation functions, but they differed in the algorithm used to iteratively adjust the synaptic weights during supervised training (see the text for details). The hidden layer of the RBF was made up of 25 centers. For each of these, the Euclidean distance between an input pattern and the center was used as an argument of a nonlinear radial basis function, and the result was passed to the output nodes, which in turn had a linear activation function. The number and coordinates of the centers in the input space and the synaptic weights of the output neurons were adjusted during supervised training.
Fmoc 5 Amino Valeric Acid 5 Ava, supplied by Chem Impex International, used in various techniques. Bioz Stars score: 95/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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19433  (LGC Standards)
99
LGC Standards 19433
(A) Schematic representation of an artificial neuron. The neuron is a simple processing unit connected to other neurons by synapses. A synaptic weight (wi) is associated with each synapsis. An output y is produced by using the weighted sum (z = Σxiwi) of its inputs (xi; x0 is fixed, and the product x0w0 is known as bias) as an argument of the activation function f(z). Different types of activation functions (nonlinear sigmoid functions as the logistic and hyperbolic tangent, but also threshold or linear functions) can be used. (B) Architecture of the ANNs used in this study. All types of networks used as an input the number of bands in selected molecular weight (in kilobases) intervals of the RAPD-PCR patterns and had three output nodes, one for each of the three species to be identified (EFM, E. faecium; EFS, E. <t>faecalis;</t> and ST, S. thermophilus). Both the MLP and the BN had a hidden layer with five nodes and used hyperbolic tangent activation functions, but they differed in the algorithm used to iteratively adjust the synaptic weights during supervised training (see the text for details). The hidden layer of the RBF was made up of 25 centers. For each of these, the Euclidean distance between an input pattern and the center was used as an argument of a nonlinear radial basis function, and the result was passed to the output nodes, which in turn had a linear activation function. The number and coordinates of the centers in the input space and the synaptic weights of the output neurons were adjusted during supervised training.
19433, supplied by LGC Standards, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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lactococcus lactis subsp cremoris atcc 19435t  (ATCC)
94
ATCC lactococcus lactis subsp cremoris atcc 19435t
(A) Schematic representation of an artificial neuron. The neuron is a simple processing unit connected to other neurons by synapses. A synaptic weight (wi) is associated with each synapsis. An output y is produced by using the weighted sum (z = Σxiwi) of its inputs (xi; x0 is fixed, and the product x0w0 is known as bias) as an argument of the activation function f(z). Different types of activation functions (nonlinear sigmoid functions as the logistic and hyperbolic tangent, but also threshold or linear functions) can be used. (B) Architecture of the ANNs used in this study. All types of networks used as an input the number of bands in selected molecular weight (in kilobases) intervals of the RAPD-PCR patterns and had three output nodes, one for each of the three species to be identified (EFM, E. faecium; EFS, E. <t>faecalis;</t> and ST, S. thermophilus). Both the MLP and the BN had a hidden layer with five nodes and used hyperbolic tangent activation functions, but they differed in the algorithm used to iteratively adjust the synaptic weights during supervised training (see the text for details). The hidden layer of the RBF was made up of 25 centers. For each of these, the Euclidean distance between an input pattern and the center was used as an argument of a nonlinear radial basis function, and the result was passed to the output nodes, which in turn had a linear activation function. The number and coordinates of the centers in the input space and the synaptic weights of the output neurons were adjusted during supervised training.
Lactococcus Lactis Subsp Cremoris Atcc 19435t, supplied by ATCC, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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s typhi atcc 19430t  (ATCC)
96
ATCC s typhi atcc 19430t
(A) Schematic representation of an artificial neuron. The neuron is a simple processing unit connected to other neurons by synapses. A synaptic weight (wi) is associated with each synapsis. An output y is produced by using the weighted sum (z = Σxiwi) of its inputs (xi; x0 is fixed, and the product x0w0 is known as bias) as an argument of the activation function f(z). Different types of activation functions (nonlinear sigmoid functions as the logistic and hyperbolic tangent, but also threshold or linear functions) can be used. (B) Architecture of the ANNs used in this study. All types of networks used as an input the number of bands in selected molecular weight (in kilobases) intervals of the RAPD-PCR patterns and had three output nodes, one for each of the three species to be identified (EFM, E. faecium; EFS, E. <t>faecalis;</t> and ST, S. thermophilus). Both the MLP and the BN had a hidden layer with five nodes and used hyperbolic tangent activation functions, but they differed in the algorithm used to iteratively adjust the synaptic weights during supervised training (see the text for details). The hidden layer of the RBF was made up of 25 centers. For each of these, the Euclidean distance between an input pattern and the center was used as an argument of a nonlinear radial basis function, and the result was passed to the output nodes, which in turn had a linear activation function. The number and coordinates of the centers in the input space and the synaptic weights of the output neurons were adjusted during supervised training.
S Typhi Atcc 19430t, supplied by ATCC, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


Bacterial strains and plasmids used in this study

Journal:

Article Title: Atypical Genetic Locus Associated with Constitutive Production of Enterocin B by Enterococcus faecium BFE 900

doi:

Figure Lengend Snippet: Bacterial strains and plasmids used in this study

Article Snippet: The immunity of L. sake DSM 20017 containing either pCMAP04 or pCMAP05 (Table ) was confirmed with the transformants as indicators in deferred inhibition assays with E. faecalis ATCC 19433 containing pCMAP03 as the producer strain.

Techniques: Plasmid Preparation, BAC Assay, Expressing

Deferred-inhibition test with E. faecalis ATCC 19433 containing pCMAP03 (EntB+) against L. sake DSM 20017 containing plasmids pMG36e (A), pCMAP04 (B), and pCMAP05 (C).

Journal:

Article Title: Atypical Genetic Locus Associated with Constitutive Production of Enterocin B by Enterococcus faecium BFE 900

doi:

Figure Lengend Snippet: Deferred-inhibition test with E. faecalis ATCC 19433 containing pCMAP03 (EntB+) against L. sake DSM 20017 containing plasmids pMG36e (A), pCMAP04 (B), and pCMAP05 (C).

Article Snippet: The immunity of L. sake DSM 20017 containing either pCMAP04 or pCMAP05 (Table ) was confirmed with the transformants as indicators in deferred inhibition assays with E. faecalis ATCC 19433 containing pCMAP03 as the producer strain.

Techniques: Inhibition

(A) Schematic representation of an artificial neuron. The neuron is a simple processing unit connected to other neurons by synapses. A synaptic weight (wi) is associated with each synapsis. An output y is produced by using the weighted sum (z = Σxiwi) of its inputs (xi; x0 is fixed, and the product x0w0 is known as bias) as an argument of the activation function f(z). Different types of activation functions (nonlinear sigmoid functions as the logistic and hyperbolic tangent, but also threshold or linear functions) can be used. (B) Architecture of the ANNs used in this study. All types of networks used as an input the number of bands in selected molecular weight (in kilobases) intervals of the RAPD-PCR patterns and had three output nodes, one for each of the three species to be identified (EFM, E. faecium; EFS, E. faecalis; and ST, S. thermophilus). Both the MLP and the BN had a hidden layer with five nodes and used hyperbolic tangent activation functions, but they differed in the algorithm used to iteratively adjust the synaptic weights during supervised training (see the text for details). The hidden layer of the RBF was made up of 25 centers. For each of these, the Euclidean distance between an input pattern and the center was used as an argument of a nonlinear radial basis function, and the result was passed to the output nodes, which in turn had a linear activation function. The number and coordinates of the centers in the input space and the synaptic weights of the output neurons were adjusted during supervised training.

Journal:

Article Title: Comparison of Statistical Methods for Identification of Streptococcus thermophilus, Enterococcus faecalis, and Enterococcus faecium from Randomly Amplified Polymorphic DNA Patterns

doi: 10.1128/AEM.67.5.2156-2166.2001

Figure Lengend Snippet: (A) Schematic representation of an artificial neuron. The neuron is a simple processing unit connected to other neurons by synapses. A synaptic weight (wi) is associated with each synapsis. An output y is produced by using the weighted sum (z = Σxiwi) of its inputs (xi; x0 is fixed, and the product x0w0 is known as bias) as an argument of the activation function f(z). Different types of activation functions (nonlinear sigmoid functions as the logistic and hyperbolic tangent, but also threshold or linear functions) can be used. (B) Architecture of the ANNs used in this study. All types of networks used as an input the number of bands in selected molecular weight (in kilobases) intervals of the RAPD-PCR patterns and had three output nodes, one for each of the three species to be identified (EFM, E. faecium; EFS, E. faecalis; and ST, S. thermophilus). Both the MLP and the BN had a hidden layer with five nodes and used hyperbolic tangent activation functions, but they differed in the algorithm used to iteratively adjust the synaptic weights during supervised training (see the text for details). The hidden layer of the RBF was made up of 25 centers. For each of these, the Euclidean distance between an input pattern and the center was used as an argument of a nonlinear radial basis function, and the result was passed to the output nodes, which in turn had a linear activation function. The number and coordinates of the centers in the input space and the synaptic weights of the output neurons were adjusted during supervised training.

Article Snippet: , Enterococcus faecalis , ATCC: 19433 T ; DBPZ: EF1; DISAABA: LC1, LC5, LC12, LC18, LC24, LC28, LC30, LC31, LC36, LP16, LP21, LP26, LP36, LP51, LP77, LP79, LP81.

Techniques: Produced, Activation Assay, Molecular Weight

List of microbial strains used in this study

Journal:

Article Title: Comparison of Statistical Methods for Identification of Streptococcus thermophilus, Enterococcus faecalis, and Enterococcus faecium from Randomly Amplified Polymorphic DNA Patterns

doi: 10.1128/AEM.67.5.2156-2166.2001

Figure Lengend Snippet: List of microbial strains used in this study

Article Snippet: , Enterococcus faecalis , ATCC: 19433 T ; DBPZ: EF1; DISAABA: LC1, LC5, LC12, LC18, LC24, LC28, LC30, LC31, LC36, LP16, LP21, LP26, LP36, LP51, LP77, LP79, LP81.

Techniques:

Performance of a supervised ANN (BN), LDA, and CT for the identification of S. thermophilus , E. faecalis , and E. faecium using simplified RAPD-PCR patterns obtained with primer XD9

Journal:

Article Title: Comparison of Statistical Methods for Identification of Streptococcus thermophilus, Enterococcus faecalis, and Enterococcus faecium from Randomly Amplified Polymorphic DNA Patterns

doi: 10.1128/AEM.67.5.2156-2166.2001

Figure Lengend Snippet: Performance of a supervised ANN (BN), LDA, and CT for the identification of S. thermophilus , E. faecalis , and E. faecium using simplified RAPD-PCR patterns obtained with primer XD9

Article Snippet: , Enterococcus faecalis , ATCC: 19433 T ; DBPZ: EF1; DISAABA: LC1, LC5, LC12, LC18, LC24, LC28, LC30, LC31, LC36, LP16, LP21, LP26, LP36, LP51, LP77, LP79, LP81.

Techniques:

Canonical score plot of simplified RAPD-PCR patterns obtained with primer XD9 for 138 strains of thermophilic streptococci. The canonical scores were calculated by discriminant analysis for the identification of S. thermophilus (○), E. faecalis (▵), and E. faecium (□) using RAPD-PCR patterns for a set of 93 strains (Table ​(Table1,1, group a). Other symbols: ♦, Streptococcus spp.; ▾, other enterococci. Open symbols correspond to patterns used for building the model; closed symbols correspond to patterns not used for building the model. The 95% confidence ellipses for the patterns of each species used for building the model are also shown.

Journal:

Article Title: Comparison of Statistical Methods for Identification of Streptococcus thermophilus, Enterococcus faecalis, and Enterococcus faecium from Randomly Amplified Polymorphic DNA Patterns

doi: 10.1128/AEM.67.5.2156-2166.2001

Figure Lengend Snippet: Canonical score plot of simplified RAPD-PCR patterns obtained with primer XD9 for 138 strains of thermophilic streptococci. The canonical scores were calculated by discriminant analysis for the identification of S. thermophilus (○), E. faecalis (▵), and E. faecium (□) using RAPD-PCR patterns for a set of 93 strains (Table ​(Table1,1, group a). Other symbols: ♦, Streptococcus spp.; ▾, other enterococci. Open symbols correspond to patterns used for building the model; closed symbols correspond to patterns not used for building the model. The 95% confidence ellipses for the patterns of each species used for building the model are also shown.

Article Snippet: , Enterococcus faecalis , ATCC: 19433 T ; DBPZ: EF1; DISAABA: LC1, LC5, LC12, LC18, LC24, LC28, LC30, LC31, LC36, LP16, LP21, LP26, LP36, LP51, LP77, LP79, LP81.

Techniques:

Dichotomic key generated by CT for the identification of S. thermophilus, E. faecalis, and E. faecium using RAPD-PCR patterns for a training set of 93 strains (Table ​(Table1,1, group a).

Journal:

Article Title: Comparison of Statistical Methods for Identification of Streptococcus thermophilus, Enterococcus faecalis, and Enterococcus faecium from Randomly Amplified Polymorphic DNA Patterns

doi: 10.1128/AEM.67.5.2156-2166.2001

Figure Lengend Snippet: Dichotomic key generated by CT for the identification of S. thermophilus, E. faecalis, and E. faecium using RAPD-PCR patterns for a training set of 93 strains (Table ​(Table1,1, group a).

Article Snippet: , Enterococcus faecalis , ATCC: 19433 T ; DBPZ: EF1; DISAABA: LC1, LC5, LC12, LC18, LC24, LC28, LC30, LC31, LC36, LP16, LP21, LP26, LP36, LP51, LP77, LP79, LP81.

Techniques: Generated

Score plot for the principal-component analysis carried out on the outputs of a BN trained to identify S. thermophilus (○), E. faecalis (▵), and E. faecium (□) using RAPD-PCR patterns for a set of 93 strains (Table ​(Table1,1, group a). The output for all 138 strains of Table ​Table11 is shown. Other symbols: ♦, Streptococcus spp.; ▾, other enterococci. Open symbols correspond to patterns used for building the model; closed symbols correspond to patterns not used for building the model. The 95% confidence ellipses for the patterns of each species used for building the model are also shown.

Journal:

Article Title: Comparison of Statistical Methods for Identification of Streptococcus thermophilus, Enterococcus faecalis, and Enterococcus faecium from Randomly Amplified Polymorphic DNA Patterns

doi: 10.1128/AEM.67.5.2156-2166.2001

Figure Lengend Snippet: Score plot for the principal-component analysis carried out on the outputs of a BN trained to identify S. thermophilus (○), E. faecalis (▵), and E. faecium (□) using RAPD-PCR patterns for a set of 93 strains (Table ​(Table1,1, group a). The output for all 138 strains of Table ​Table11 is shown. Other symbols: ♦, Streptococcus spp.; ▾, other enterococci. Open symbols correspond to patterns used for building the model; closed symbols correspond to patterns not used for building the model. The 95% confidence ellipses for the patterns of each species used for building the model are also shown.

Article Snippet: , Enterococcus faecalis , ATCC: 19433 T ; DBPZ: EF1; DISAABA: LC1, LC5, LC12, LC18, LC24, LC28, LC30, LC31, LC36, LP16, LP21, LP26, LP36, LP51, LP77, LP79, LP81.

Techniques: